🎬 AI Video Workspace

reelbench-skills

Claude Code / Codex skills for working with video.

skill	what it does
video-shots	Shot breakdown: turns a finished film into a shot-by-shot table — duration, shot size, category, camera move, frame description, rhythm role. Cuts and durations are measured by ffmpeg; the model only judges what it should; 15 quality gates check every call.
video-sync	Composites a video with the shot data alongside it: footage on one side, the current shot's data on the other, switching at every cut with the list scrolling and highlighting itself. Landscape stacks, portrait sits side by side; the layout is one CSS file.
video-scrub	Strips metadata: rebuilds the film as a clean file carrying only picture and sound — GPS, device, account IDs and telemetry tracks all left behind. The hard part is the three layers ffprobe cannot see: SEI, the AAC DSE, and compressorname. Byte-for-byte picture by default, verified by 12 byte-level gates.

AI video community

I run a paid group about AI video — workflows, tools, and how this stuff actually gets done.

Interested? Message me on Telegram @ahao_dev and mention github.

Install

git clone https://github.com/eternityspring/reelbench-skills.git
cd reelbench-skills
./scripts/install.sh

This symlinks the skills into ~/.claude/skills/ and/or ~/.codex/skills/ (whichever exists), so git pull takes effect immediately.

./scripts/install.sh --claude      # Claude Code only
./scripts/install.sh --codex       # codex only
./scripts/install.sh video-shots   # one skill only
./scripts/install.sh --uninstall   # remove the symlinks

Requirements: node >= 18 and ffmpeg / ffprobe (macOS: brew install node ffmpeg). No npm dependencies, no API keys — it runs on your current session.

Prefer a copy over a symlink? cp -r skills/video-shots ~/.claude/skills/ — each skill is self-contained.

Example

demo-report/ is the real output of running the skill on demo-video.mp4 (a 202.9-second AI-generated short film, 啥是AI): 53 shots, 3.83 s average shot length, 15.7 cuts per minute, all 15 gates green. demo-report-en/ is the same pipeline run on a 287.4-second English excerpt with --lang en — an entirely English report: 46 shots, 6.25 s average, and one 46.92 s take that scene detection never cut, because it genuinely never cuts.

The report is a single interactive page: an embedded player (playback highlights the current shot, click a shot to jump), a pace strip, a shot list you can search, filter and sort (list or card view, first and last keyframe side by side, click a frame to enlarge), distributions, cast, and the quality gates. No external dependencies — double-click it offline.

demo-report/
├── shots-report.html   ← clone and double-click
├── shots.json          ← the breakdown data for all 53 shots
├── shots.md            ← Markdown shot list
├── track.json          ← frame-difference motion curve (the machine's evidence)
└── frames/             ← first and last keyframe of every shot, 106 files